Update julialang.md

docs.it4i/software/lang/julialang.md

 # JuliaLang
 
-Set of unofficial examples of Julia the high-level, high-performance dynamic programming language for technical computing.
+A set of unofficial examples of Julia the high-level, high-performance dynamic programming language for technical computing.
 
-Below are a series of examples of common operations in Julia. They assume you already have Julia installed and working
+Below are examples of common operations in Julia. They assume you already have Julia installed and working
 
 ## Hello World
 
-The simplest possible script.
+The simplest possible script:
 
 ```c
 println("hello world")
@@ -14,7 +14,7 @@ println("hello world")
 
 With Julia [installed and added to your path](http://julialang.org/downloads/)
 this script can be run by `julia hello_world.jl`, it can also be run from REPL by typing
-`include("hello_world.jl")`, that will evaluate all valid expressions in that file and return the last output.
+`include("hello_world.jl")`, which will evaluate all valid expressions in that file and return the last output.
 
 ## Simple Functions
 
@@ -58,7 +58,7 @@ println("result 2: ", quad2)
 
 ## Strings Basics
 
-Collection of different string examples (string indexing is the same as array indexing: see below).
+Collection of different string examples (string indexing is the same as array indexing, see below):
 
 ```c
 # strings are defined with double quotes
@@ -347,7 +347,7 @@ println("Continuing after error")
 ## Multidimensional Arrays
 
 Julia has very good multidimensional array capabilities.
-Check out [the manual](http://julia.readthedocs.org/en/latest/manual/arrays/).
+See [the manual](http://julia.readthedocs.org/en/latest/manual/arrays/).
 
 ```c
 # repeat can be useful to expand a grid
@@ -449,7 +449,7 @@ end
 ## Dictionaries
 
 Julia uses [Dicts](http://docs.julialang.org/en/latest/stdlib/base/#associative-collections) as
-associative collections. Usage is very like python except for the rather odd `=>` definition syntax.
+associative collections. Usage is similar to Python except for the `=>` definition syntax.
 
 ```c
 # <hide>
@@ -618,7 +618,7 @@ println(fam2)
 
 ## Input & Output
 
-The basic syntax for reading and writing files in Julia is quite similar to python.
+The basic syntax for reading and writing files in Julia is quite similar to Python.
 
 The `simple.dat` file used in this example is available
 [from github](https://github.com/samuelcolvin/JuliaByExample/blob/master/src/simple.dat).
@@ -674,7 +674,7 @@ println(repr(outfile_content))
 ## Packages and Including of Files
 
 [Packages](http://docs.julialang.org/en/latest/packages/packagelist/)
-extend the functionality of Julia's standard library.
+extend the functionality of the Julia's standard library.
 
 ```c
 # You might not want to run this file completely, as the Pkg-commands can take a
@@ -711,7 +711,7 @@ Calculus.derivative(x -> cos(x), 1.0)
 
 [Winston Package Page](https://github.com/nolta/Winston.jl)
 
-Matlab-like plotting. Installed via `Pkg.add("Winston")`
+MATLAB-like plotting. Installed via `Pkg.add("Winston")`
 
 ```c
 using Winston
@@ -731,7 +731,7 @@ savefig("winston.svg")
 
 ## DataFrames
 
-The [DataFrames.jl package](https://github.com/JuliaStats/DataFrames.jl) provides tool for working with tabular data.
+The [DataFrames.jl package](https://github.com/JuliaStats/DataFrames.jl) provides a tool for working with tabular data.
 
 The `iris.csv` file used in this example is available
 [from github](https://github.com/samuelcolvin/JuliaByExample/blob/master/common_usage/iris.csv).

[Jan Siwiec]

relates to #70